Utilization of Artificial Neural Network for the Protection of Power Transformer

Banerjee, Mudita; Khosla, Anita

doi:10.1007/978-981-15-0633-8_45

Cited by 2 publications

(1 citation statement)

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“…Main task of Wavelet transform is the extraction and decomposition of transient signal into various resolution levels [10]. Recently, extensive research is going on differentiation techniques based on Artificial Intelligence like Fuzzy logic [11], Artificial neural network [12][13], Probabilistic neural network, Fuzzyneuro hybrid intelligent system [14]. The cited researchers have developed the differentiation algorithm for the protection, which increases the speed and robustness of present digital relays [15].…”

Section: Introductionmentioning

confidence: 99%

Differential Protection of Power Transformer using Wavelet Transform

Banerjee*¹,

Khosla²

2019

IJRTE

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 Abstract: This paper presents wavelet transform method for the analysis of differential currents of power transformer which can act as an accurate classifier between magnetizing inrush current and internal faults to avoid the needless tripping of circuit breaker. The differential protection scheme occasionally maloperate whenever magnetizing inrush occurs in power transformer. The aim is to reduce the rate and time duration of undesired outages of power transformer. This includes the necessities of reliability with zero maloperation of differential relay. The result shows higher operating speed with less fault clearing time. Wavelet Transform is employed for the analysis of transient signals under various conditions, which extracts data from signals in time and frequency domain simultaneously. The simulation is done in MATLAB environment.

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Section: Introductionmentioning

confidence: 99%